Title

Decoding Brain States Based on Magnetoencephalography From Prespecified Cortical Regions

Document Type

Article

Abstract

Brain state decoding based on whole-head MEG has been extensively studied over the past decade. Recent MEG applications pose an emerging need of decoding brain states based on MEG signals originating from prespecified cortical regions. Toward this goal, we propose a novel region-of-interest-constrained discriminant analysis algorithm (RDA) in this paper. RDA integrates linear classification and beamspace transformation into a unified framework by formulating a constrained optimization problem. Our experimental results based on human subjects demonstrate that RDA can efficiently extract the discriminant pattern from prespecified cortical regions to accurately distinguish different brain states.

Medical Subject Headings

Algorithms; Cerebral Cortex (physiology); Computer Simulation; Discriminant Analysis; Humans; Magnetoencephalography (classification, methods); Signal Processing, Computer-Assisted

Publication Date

1-1-2016

Publication Title

IEEE transactions on bio-medical engineering

E-ISSN

1558-2531

Volume

63

Issue

1

First Page

30

Last Page

42

PubMed ID

26699648

Digital Object Identifier (DOI)

10.1109/TBME.2015.2439216

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